A variant of the NSGA II for the speed scaling distributed flow shop scheduling problem with total tardiness minimisation

Abstract

In this study, an energy-efficient distributed flow shop scheduling (DFSS) problem with total tardiness minimisation and machine-sequence dependent setup times is addressed. A mixed integer linear programming (MILP) model is proposed for the problem. A variant of the NSGA II algorithm is suggested for the solution of large scale problems. The proposed algorithm is compared with the state-of-the-art NSGA II, SPEA II, and multiobjective iterated local search algorithm. The computational results show that the proposed algorithm is efficient and effective for the problem. This is the first study to propose a heuristic algorithm for the distributed flow shop scheduling problem with total tardiness minimisation, speed scaling and setups.